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none 4 si Bilateral trade flows traditionally have been analysed by means of the spatial interaction gravity model. Still, (auto)correlation of trade flows has only recently received attention in the literature. This paper takes up this thread of emerging literature, and shows that spatial filtering (SF) techniques can take into account the autocorrelation in trade flows. Furthermore, we show that the use of origin and destination specific spatial filters goes a long way in correcting for omitted variable bias in an otherwise standard empirical gravity equation. For a cross-section of bilateral trade flows, we compare an SF approach to two benchmark specifications that are consistent with theoretically derived gravity. The results are relevant for a number of reasons. First, we correct for autocorrelation in the residuals. Second, we suggest that the empirical gravity equation can still be considered in applied work, despite the theoretical arguments for its misspecification due to omitted multilateral resistance terms. Third, if we include SF variables, we can still resort to any desired estimator, such as OLS, Poisson or negative binomial regression. Finally, interpreting endogeneity bias as autocorrelation in regressor variables and residuals allows for a more general specification of the gravity equation than the relatively restricted theoretical gravity equation. In particular, we can include additional country-specific push and pull variables, besides GDP (e.g., land area, landlockedness, and per capita GDP). A final analysis provides autocorrelation diagnostics according to different candidate indicators. R. Patuelli; G.-J.Linders; R. Metulini; D.A. Griffith R. Patuelli; G.-J.Linders; R. Metulini; D.A. Griffith

Recently, an investigation of unobserved and time-varying multilateral resistance and omitted trade determinants has assumed a prominent role in order to precisely measure the Euro effects on trade. We implement two methodologies: the factor-based gravity model by Serlenga and Shin (The Euro Effect on Intra-EU Trade: Evidence from the Cross Sectionally Dependent Panel Gravity Models, Mimeo, University of York, 2013) and the spatial-based techniques by Behrens et al. (J Appl Econ 27:773–794, 2012), both of which allow trade flows and error terms to be cross-sectionally correlated. Applying these approaches to the dataset over 1960–2008 for 190 country-pairs of 14 EU and six non-EU OECD countries, we find that the Euro impact estimated by the factor-based model amounts to only 4–5 %, far less than the 20 % estimated by the spatial-based model. The cross-section dependency test results also confirm that the factor-based model is more appropriate in accommodating correlation between regressors, and unobserved individual and time effects. Overall we may conclude that the trade-creating effects of the Euro should be viewed in the proper historical and multilateral perspective rather than in terms of the formation of a monetary union as an isolated event.